The 12th International Symposium on Advanced Intelligent Systems (ISIS 2011) held at La Vie DfOr Resort, Suwon, Korea, on September 28 to October 1, 2011, featured presentations by researchers, engineers and practitioners on the latest accomplishments, innovations and applications in artificial intelligence, intelligent systems, and information technology. The 152 papers consisted of 110 regular papers, 39 organized session papers and 3 invited papers were contributed to the conference. The Program Committee requested ISIS 2011 reviewers to select papers for a special issue of the Journal of Advanced Computational Intelligence & Intelligent Informatics (JACIII), of which about 10 were accepted for publication in a twopart ISIS 2011 special issue, Vol.16, No.7, containing 5 papers. Part II will feature about 5 papers.

A brief review of Part I covers 5 papers:

First paper proposes a quantitative model for assessing the collision risk in maritime waterway traffic. The method proposes recent maritime traffic characteristics in time-variant CPA waterway environments and models a dynamic causation factor as a risk indicator. Second paper proposes multiagent query refinement realizing personalized query refinement by three strategies ? knowledge-based query expansion, user-device-based query and weighted query expansion strategy. These approaches determine the domain that the initial query belongs to and expand the query by comprehensively considering user interests. Third paper presents variable-step-size incremental conductance direct maximum power point tracking using fuzzy membership for a standalone photovoltaic system under rapidly changing irradiation. Fourth paper applies a natural actor-critic (NAC) and natural evolution strategies (NES) from natural-gradient-based machine learning to path-tracking control problems for autonomous vehicles. Fifth paper presents features for authenticating painting style, specifically that of Piet Mondrain. It demonstrates meaningful features using two supervised learning algorithms ? decision tree induction algorithm C4.5 and the feature generating machine (FGM) ? selecting important features in the course of learning.

We thank the reviewers for their time and effort in making this special issue available so quickly. We are also grateful to the JACIII editorial office for invaluable assistance and advice in putting the issue together.

On February 22, 2010, Prof. Ebrahim H. Mamdani who devised Mamdani fuzzy inference has passed away. His work in fuzzy inference, which rapidly paved the way to its practical use, helped disseminate Prof. Lotfi Zadehfs fuzzy logic and the development of fuzzy research.

Prof. Mamdanifs two papers on fuzzy inference ? gApplication of fuzzy algorithms for control of simple dynamic planth (Proc. IEE, Vol.121, No. 12, pp. 1585-1588, 1974) and gAn experiment in linguistic synthesis with a fuzzy logic controllerh (Int. J. of Man-Machine Studies, Vol.7, No.1, pp. 1-13, 1975) with S. Assilian ? enabled fuzzy inference technology to develop dramatically both indicatively and indirectly to where it has been applied, including fuzzy control systems.

This special issue honors Prof. Mamdani for his invaluable efforts in these and many other fields. We have asked for submissions by researchers influenced by Prof. Mamdanifs achievements, including his work in fuzzy inference, and have narrowed down to one review and seven full papers. The review by Hirosato Seki and Kai Meng Tay provides an incisive overview on the many aspects of fuzzy inference that Prof. Mamdani brought to light.

Prof. Mamdanifs fuzzy inference has become a deterministic technology that can be chosen naturally and that will continue to be influential and survivable well into the future.

Modeling and simulation play pivotal roles in engineering design. Tools for modeling and simulation have led to both faster design, higher viability and lower design cost. This special issue presents 10 papers on modeling and simulation in a variety of applications.

The first paper, by Sayed Mohammad Reza Loghmanian et al., is entitled gNonlinear Dynamic System Identification Using Volterra Series: Multi-Objective Optimization Approach.h This paper deals with system identification of the nonlinear dynamic system based on an optimized Volterra model structure. The developed model fulfilled two criteria, or objectives, namely, good predictive accuracy and optimum model structure. Genetic algorithms are applied to search for significant Volterra kernels among all possible candidate model combinations.

The second paper, by Masao Ogino et al., is entitled gA Large-Scale Magnetostatic Analysis Using an Iterative Domain Decomposition Method Based on the Minimal Residual Method.h Large-scale 3D nonlinear magnetostatic analysis using the domain decomposition method (DDM) improves convergence based on the conjugate residual (CR) method. Compared to the conjugate gradient method, the CR method and minimal residual method both improve the convergence rate and show stable convergence behavior in solving an interface problem. Computation time is largely reduced for this large-scale problem, which has about 10 million degrees of freedom.

The third paper, by Yoshiyuki Yamashita, is on gSemi-Qualitative Trend Analysis for the Monitoring of Process Control Loops,h and deals with a qualitative approach, rather than an analytical approach, in monitoring process plants. Using this method enabled us to diagnose a control valve problem in a process control loop. Several applications are also discussed.

The fourth paper, by Hiroshi Dan and Hiroshi Kanayama, is entitled gFinite Element Analysis of Tsunami by Viscous Shallow-Water Equations.h With the number of tsunamis and earthquakes occurring worldwide today, such simulation is important in many fields. Viscous shallow-water equations are derived from three-dimensional Navier-Stokes equations under hydrostatic assumptions. This approach is used to simulate a tsunami in Hakata Bay.

The fifth paper, by Junzo Watada et al., is entitled gAn Affective Approach to Developing Marketing Strategies of Mineral Water.h This research concerns the development of a marketing strategy for mineral water based on taste features obtained by chemically and physically analyzing the taste components of mineral water. Two-dimensional analysis of self-organizing map (SOM) was used to classify the evaluation of taste data. Data characteristics are recognized in the taste of mineral water by correlation analysis. A combination of principal component analysis and SOM classifies the taste of mineral water. Marketing strategies are also concluded after evaluation.

The sixth paper, by Yoshitsugu Aoki et al., is entitled gNew Approach for Antisense Oligonucleotide-Mediated Exon Skipping in Duchenne Muscular Dystrophy.h It reviews highlights of the challenges in antisense oligonucleotide-based therapeutics for treating and Intelligent Informatics DMD, focusing on exon 51-skipping.

The seventh paper, entitled gBuilding a Type-2 Fuzzy Qualitative Regression Model,h is by Yicheng Wei and Junzo Watada. From a theoretical fuzzy-set point of view, uncertainty exists in the membership function value of a type-1 fuzzy set, greatly impacting on the fuzziness of the external criterion of the qualitative objective. This paper models qualitative change in the external criterionfs fuzziness by applying the type-2 fuzzy set. Here, qualitative values are assumed to be fuzzy degrees of membership in qualitative categories, and qualitative change in the objective external criterion is given as the fuzziness of output.

The eighth paper, entitled gPSO-Particle Filter-Based Biometric Measurement for Human Tracking,h is by Zhenyuan Xu and Junzo Watada. It discusses an interesting application based on particle swarm optimization (PSO). Its objective is to build a mathematical model and a method for human tracking that can be used for biometric surveillance. This human tracking marks the size of human beings and objects in a picture to that if the picture is placed in a framework of axes, height and other biometric lengths can be calculated.

The ninth paper, by Josu? Roberto Lozano et al. is on g360 Degree Selective Laser Trabeculoplasty in Mexican Population.h This research uses statistical analysis of Repeated Measures One-Sample T Test, Paired-Samples T Test + Pearson Correlation Coefficient Test, and the Wilcoxon Signed-Rank Test in order to evaluate the efficiency of Selective Laser Trabeculoplasty procedure (SLT procedure). The authors showed in the paper that the treatment with SLT applied to Mexican patients with OAG reduces IOP and the patientfs need for topical medical therapy, which can lead to a better control of the disease and compliance to treatment.

The tenth paper, by Shinichiro Terasaki and Shinfya Nagasawa, is on gThe Relationship Between Brand Integrity and Business Continuity ? A Case Study of Japanese Long-Standing Company, Shioyoshiken ?.h The Shioyoshiken brand of Japanese sweets is well appreciated by individual customers who emphasise the value of customized sweets, particularly for Japanese tea parties and weddings. This case study explores Shioyoshiken gRashisa,h or gidentity,h to identify the secret of its long-standing brand strength.

With broadband networks, audio/video coding, and processing techniques and user devices swiftly advancing, multimedia streaming over networks is now a reality. Distributed interactive multimedia applications ? one of the fastest growing market sectors demanding innovations ? are covered in this special issue on multimedia processing (MP).

This special issue focuses on ambitious and intriguing papers from experts on a wide variety of multimedia areas. These articles address innovations and offer effective solutions to MP problems.

Y. Fushio et al. propose a shadow generation system based on shape recognition, while M. Suzuki et al. develop musical expression generation reflecting the userfs impression in kansei space and fuzzy rules. K. Ishizuka et al. evaluate an operetta songs generation system based on the impressions given by story scenes, which are strongly related to the integrative research projects of kansei engineering, music, text, and visual perception.

T. Toyota et al. develop a web news visualization system based on an efficient self-organizing map using a restricted region search and dimensionality reduction. S. Kawauchi et al. propose a knowledge expansion support system using related search keyword generation based on Wikipedia categories and point-wise mutual information, involving that are aggressive looking progressive research projects covering huge text information. T. Tanabata et al. present an interactive data mining tool for microarray data analysis using formal concept analysis, which adds a new dimension to the bio-informatics field.

T. Kawamura et al. analyze keywords input to a book search engine. T. Sugimoto et al. propose a recommendation system involving the use of comprehensive trend indications based on weighted complete graphs, which are related to topical discussions in the information retrieval and recommendation field.

Readers are sure to find new and valuable information and ideas in their own fields in these excellent articles.

Cognitive infocommunications (CogInfoCom), is an emerging interdisciplinary research field that has recently started to appear in the context of theoretical, R&D, and industryoriented projects. CogInfoCom deals with novel approaches to extend the cognitive capabilities of human users through the artificial cognitive capabilities of infocommunications devices, enabling them to interact more flexibly with IT infrastructure.

Two key points must be considered when asking why the emergence of CogInfoCom is not only timely but also necessary.

First of all, the infocommunications industry is experiencing trends that are resulting in the gradual appearance of artificial cognitive capabilities ? capabilities directed towards a broadened scope covering the sensing and processing of unstructured data.

Secondly, future users of infocommunications devices will expect both to be able to access these artificial cognitive capabilities in their everyday activities and to be able to merge them with their own cognitive capabilities. They will thus be able to apply them flexibly ? through their infocommunications devices ? in a wide range of applications in both physical and virtual contexts.

This Special Issue on Cognitive Infocommunications contains extended versions of key ideas presented at CogInfoCom conferences. The table of contents alone will demonstrate to the reader the broad scope of theoretical considerations and practical applications that underlie current and emerging CogInfoCom research.

It is our hope that this Special Issue ? along with the CogInfoCom conference series ? will contribute to providing a scientific forum for researchers from areas related to CogInfoCom and beyond, so that they may be able to develop stronger cooperation and create a more common language in order to produce useful synergies, and in order to fully meet the interdisciplinary challenges that underlie CogInfoCom.

One important and interesting application in computational intelligence technology is medical application. Medical engineering research covers such areas as medical image processing. With most health information now described electronically, hospitals are accumulating large amounts of medical data, including imaging, text, and structured materials. This has made ginformation medical scienceh vastly more important in improving healthcare technology.

This special issue introduces an application based on hospital data, medical care support systems, and medical image processing. The application deals with analytical approaches, navigation systems, medical data management, and text mining for summary data. The support system shows diagnosis and robotassisted therapy. Medical imaging targets X-ray, blood cell, and ultrasonography images.

As guest editors, we can assure the readers that the papers in this special issue have great social impact in this research area and encourage good relations with engineering and medical practice approaches.

We thank the contributors and reviewers for introduce these latest achievements in this exciting field.

Six papers on Human Machine Interfaces have been published from a new point of view. As one of the important technologies for developing optimal human machine interaction, communication between humans and machines has attracted much interest. In this special issue, the editor focuses on new methods for communicating mutual information on the characteristics of both human operators and machines, including computers and vehicles. In this communication, readers can operate machines easily and comfortably.

The first article, by Hiroshi Takahashi and Hirohiko Honda, studies the possibility of applying subliminal visual marks for informing drivers of hazardous factors without causing a nuisance in the driver-assistance systems.

The second paper, by Hiroshi Igarashi, proposes subliminal control parameter calibration in interactive human-machine operational environments. Subliminal calibration will enable users to master handling in a short time.

The third paper, by Hiroshi Takahashi and Hirohiko Honda, focuses on computer game operation as influenced by ultrasound exposure. The relationship between ultrasound signals and operator behavior is discussed.

The fourth paper, written by Hirohiko Honda and Kazuko Tobita, concerns the improvement of personal computer operation using auditory signals for visually handicapped persons, who can then identify operational processes through simple sounds.

The fifth contribution, by Hirohiko Honda, involves improving mouse operation with personal computers for those physically challenged who suffer progressive deterioration. The proposed system helps such users maintain quality of life because they are able to continue using a personal computer even as their state of mobility deteriorates.

The closing contribution, by Hiroshi Igarashi, Yoshinobu Adachi, and Kazunari Takahashi, deals with multiagent systems based on human social behavior. Adaptability and the total performance of the authorfs proposed technique are confirmed through a pursuit problem in a multiagent system.

We thank the referees for their reviews and the Fuji Technology Press Ltd. staff for its encouragement and advice.

This issue features decision making and other tools used in artificial intelligence applications. More specifically, the issue includes five papers focused on aggregation operators and clustering.

The series starts with a paper by Yoshida on weighted quasiarithmetic means that focuses on their monotonicity viewed from utility and weighting functions.

In the second paper, Nohmi, Honda and Okazaki focus on trust evaluation for networks, studying matrix operations based on t-norms and t-conorms. The authors also propose fuzzy graphs using adjacent matrices.

These works are followed by three on fuzzy clustering.

Kanzawa, Endo and Miyamoto present a variation of fuzzy c-means based on kernel functions in an approach developed for data with tolerance.

Endo covers clustering using kernel functions. The paper is based on a fuzzy nonmetric model including pairwise constraints in the clustering process.

The concluding paper also uses pairwise constraints, but within agglomerative hierarchical clustering. Hamasuna, Endo and Miyamoto include clusterwise tolerance in their mode.

As the editors of this issue, we would like to thank the referees for their work in the reviews and journal editors-in-chief Profs. Toshio Fukuda and Kaoru Hirota and the journal staff for their support.

As awareness computing attracts increasing attention, this special issue has been arranged for researchers, engineers, and scientists to discuss on awareness computing and to exchange ideas, opinions, and the latest results in this emerging new field.

Awareness is the ability to be conscious of, feel, or perceive ? in other words, to have awareness. It implies vigilance in observing and alertness in drawing inferences from experience. The ultimate goal of awareness computing is to create computing systems that are aware.

The eight papers accepted for this issue come mainly from International Symposium on Aware Computing 2010 and cover different aspects of awareness computing in science and engineering. The authors have been kind enough to revise their papers for this publication.

Two papers focus on awareness learning and multimedia-based learning, three examine localization using sensor networks, sound sources, and radiofrequency identification, and three explore a fuzzy-rules mining algorithm, an interactive map search system, and semi-supervised method for pattern recognition.

We thank the reviewers for their time and effort in reviewing papers within a limited time. We are most grateful to Professor Qiangfu Zhao of the University of Aizu, Japan, and to Professors Toshio Fukuda and Kaoru Hirota, Editors-in-Chief, for inviting us to guest-edit this special issue. We also thank the Fuji Technology Press staff for its ongoing assistance.

The Second World Congress on Nature and Biologically Inspired Computing (NaBIC2010) was held at the Kitakyushu International Conference Center December 15-17, 2010, in Kitakyushu, Japan. NaBIC2010 provided a forum for researchers, engineers, and students from worldwide to discuss state-of-the-art machine intelligence and to address issues related to building human-friendly machines by learning from nature.

NaBIC2010 covered a wide range of studies ? from theoretical and algorithmic studies on nature and biologically inspired computing techniques to their real-world applications.

Top researchers presenting papers at NaBIC2010 were invited to contribute to this special issue. Through a fair peer review process, four extended papers have been accepted ? an acceptance rate of 50%.

The first paper entitled gA Study on Computational Efficiency and Plasticity in Baldwinian Learningh by Liu and Iba analyzes Baldwinian evolution efficiency by comparing it to alternatives such as standard Darwinian evolution with no learning, Lamarckian evolution, and Baldwinian evolution with different learning and plasticity evolution.

The second paper entitled gExperimental Study of a Structured Differential Evolution with Mixed Strategiesh by Ishimizu and Tagawa proposes island-based DE with ring or torus networks. The authors examine the performance of the proposed DE with the effects of different strategies.

The third paper entitled gMulti-Space Competitive DGA for Model Selection and its Application to Localization of Multiple Signal Sourcesh by Ishikawa, Misawa, Kubota, Tokiwa, Horio, and Yamakawa proposes a distributed genetic algorithm in which each subpopulation searches for a solution in different decision space. Subpopulations change size based on search progress.

The fourth paper entitled gAn Extended Interactive Evolutionary Computation Using Heart Rate Variability as Fitness Value for Composing Music Chord Progressh by Fukumoto, Nakashima, Ogawa, and Imai uses heart-rate variability instead of direct human evaluations in an interactive evolutionary computation framework.

As guest editors of this special issue, we would like to thank the authors for their unique and interesting contributions and the reviewers for their careful checking and invaluable comments.

Expertise in sports, music, dance, and craftsmanship is increasingly attracting researchers from many different backgrounds who seek to deepen their understanding of outstanding human skills – a field known as skill science. The goal of skill science is to elucidate neural, cognitive, and computational mechanisms and processes underlying superior sensorimotor functions. To this aim, cross-disciplinary approaches needed include artificial intelligence, computational intelligence, soft computing, robotics, biomechanics, cognitive science, and neuroscience.

This special issue includes a variety of paper focusing on new computational approaces and cutting-edge empirical techniques shedding light on embodied knowledge. Analytical techniques include factorial analysis, such as Principal Component Analysis (PCA) and Singular Vector Decomposition (SVD), correlation networks, machine learning such as cluster analysis, Bayesian statistics, and nonlinear dynamical modeling. Experimental paradigms and techniques include Virtual Reality (VR) environment, comparison between skilled and unskilled individuals and between individuals with and without neurological disorders, and biomechanical and physiological measurement using motion capture, ElectroMyoGraphy (EMG), functional Magnetic Resonance Imaging (fMRI), Transcranial Magnetic Stimulation (TMS), and Auditory Brainstem Response (ABR).

These approaches and techniques have successfully addressed key features of sensorimotor mechanisms behind skilled human behavior. Unique approaches in terms of abduction reasoning and observation learning of robots have quantitatively and qualitatively unraveled cognitive processes in novel skill acquisition.

Findings from these studies provide intriguing insights into developing comprehensive models of embodied knowledge and into practical applications Quantitative evaluation and precise modeling of human skills are, for example, indispensable for developing hardware and software that mimic human functions and for designing robots and Brain-Machine Interfaces (BMI) that enables dexterous human-like behavior. It is of academic and clinical importance to determine mechanisms for acquiring complex sensorimotor skills. These diverse approaches toward a unique goal are expected to build bridges among researchers with vastly different backgrounds, serving as an impetus for boosting this cross-disciplinary research area.

We believe this special issue will serve as a landmark for further developing skill science research.

This second special issue from the Joint 5th International Conference on Soft Computing and Intelligent Systems and the 11th International Symposium on Advanced Intelligent Systems (SCIS & ISIS) 2010 presents 11 progressive papers covering topics from Fuzzy c-Means, clustering, evolutionary algorithms, and self-organizing maps to optimization, spiral phenomena, matroids, multirobot systems, and reinforcement learning. This wide range of research interests reflects current trends in the SCIS & ISIS conference series. As such, they demonstrate how near-future research interests are gradually moving toward exciting new directions.

We thank the authors and reviewers for taking time out from their busy schedules to make this publication possible. We are especially grateful to Prof. Toshio Fukuda of Nagoya University and to Prof. Kaoru Hirota of the Tokyo Institute of Technology for giving us the opportunity to guest-edit JACIII. Our special thanks go to Ms. Reiko Ohta of Fuji Technology Press Ltd. for her ongoing support in publication.

This special issue features the selected papers from i-SAIRAS 2010 (The 10th International Symposium on Artificial Intelligence, Robotics and Automation in Space) at Sapporo, Japan on August 29 – September 1, 2010), which explores the technology of Artificial Intelligence (AI), Automation and Robotics, and its application in space. In the AI domain, in particular, i-SAIRAS focuses on the following issues: (1) spacecraft autonomy (e.g., inboard software for mission planning and execution, resource management, fault protection, science data analysis, guidance, navigation and control, smart sensors, testing and validation, architectures); (2) mission operations automation (e.g., decision support tools for mission planning and scheduling, anomaly detection and fault analysis, innovative operations concepts, data visualization, secure commanding and networking); (3) design tools and optimization methods, electronic documentation; and (4) AI methods (e.g., automated planning and scheduling, agents model-based reasoning, machine learning and data mining).

In the selection process for JACIII (Journal of Advanced Computational Intelligence and Intelligent Informatics), 13 papers were firstly nominated from 133 oral presentation papers as outstanding AI-related papers by i-SAIRAS International Committee, and 6 papers were finally accepted through the two-stages of pear-reviews. All papers were reviewed by three reviewers. As the brief introduction of these papers, the paper by Mark Johnston and Mark Giuliano presents an architecture called MUSE (Multi-User Scheduling Environment) to integrate multi-objective evolutionary algorithms with existing domain planning and scheduling tools. The second paper by Amdeo Cesta et al. discusses general lessons learned from a series of deployed planning and scheduling systems. The third paper by Alessandro Donati et al. spotlights specific achievements and trends in the area of spacecraft diagnosis and mission planning and scheduling. The fourth paper by Cedric Cocaud and Takashi Kubota proposes the system that provides position and attitude information to a spacecraft during its approach descent and landing phase toward the surface of an asteroid. The firth paper by Tomohiro Harada et al. studies On-Board Computer which evolves computer programs through the bit inversion and analyzes its robustness to the bit inversion. Finally, the last paper by Masayuki Otani et al. explores the distributed control of the multiple robots which may be broken in the assembly of space solar power satellite. The editor hopes that these papers would help for readers to capture the state-of-art of AI technology in space.

When the computer revolution began in the second half of the 20th century, few could have foreseen the pervasiveness that intelligent devices would have only half a century later. Today, consumers deal with numerous computing devices providing increasingly sophisticated services. Arguably, no other invention has so profoundly impacted on daily home and work lives as the computer. The downside, however, holds the worrying realization that many artifacts of modern technology now touch on the human sphere to the point of risking an individualfs privacy, security, and well-being.

The new millennium carries the computer revolution to unprecedented levels where new computing paradigms excite researchers beyond the limits of science fiction. The burgeoning field of synthetic biology, for example, has given rise to novel computing approaches based on biomolecular materials. Indeed, silicon is no longer the only substrate for intelligent information processing. Other unconventional approaches such as computing with slime molds, for example, now embrace even living organisms. Information processing and problem solving strategies observed in nature have inspired the design of novelmachine learning algorithms. Seemingly unlimited computer power now enables the in silico simulation of living organisms and the study of evolutionary processes with enormous efficiency. Although many of these novel, nature-inspired approaches are still in their infancy, they might bring a paradigm shift in computational science. How such a technology-driven paradigm shift may affect the gsofth components of our modern complex society is a many-faceted issue that deserves our consideration and exploration.

This special issue focuses on new developments in intelligent computing. A. Schuster and D. Berrar analyze the potentials and risks of current and emerging intelligent computing paradigms. Their article focuses on the interface between humans and intelligent systems and explores potentials and risks emerging for individuals and for the information society at large.

L. Palafox and H. Hashimoto propose a new human activity recognition system that relies on the analysis of five key variables to categorize human activities. A prototypical implementation of the system demonstrates promising results for applications in intelligent room settings.

M. Kimura and M. Sugiyama propose a novel approach to unsupervised clustering, which is based on least squares mutual information. The advantage of this approach is that hyperparameters of clustering algorithms such as kernel parameters no longer need to be manually calibrated, but they can be automatically optimized.

D. Ricinschi and E. Tokumitsu explore new ways of exploiting physical properties of ferroelectric materials. They investigate how the amount of polarization generated by two electrical pulses can be modeled and explained in the framework of game theory.

This special issue informs the research community about exciting new developments in intelligent computing, with an outlook on their societal impacts.

SCIS & ISIS is a biennial international joint conference on soft computing and intelligent systems, with research ranging from fuzzy systems, neural networks, and evolutionary computation to multi-agent systems, artificial intelligence, and robotics.

SCIS & ISIS 2010 consisted of the 5th International Conference on Soft Computing and Intelligent Systems (SCIS) and the 11th International Symposium on Advanced Intelligent Systems (ISIS), held at Okayama Convention Center on December 8-12, 2010. Original presentations numbered 302 and participants 322.

After preliminary selection by SCIS & ISIS 2010 session chairs, we listed over 70 papers to be published in extended form in the Special Issue of the Journal of Advanced Computational Intelligence and Intelligent Informatics. After inviting these authors to submit papers for this special issue, we had two referees to review them and accepted 27 for publication in Vol.15, Nos.7 and 8 in 2011.

This special issue presents 15 of these papers covering most conference topics, including fuzzy theory, learning methods, neural networks, and evolutionary computation, with a focus on reinforcement learning, multi-agent system, nonlinear estimation, and real-world applications to visual system, robotics and energy.

We thank the authors and reviewers for their invaluable contributions toward making this special issue possible. We are also grateful to Editors-in-chief Prof. Toshio Fukuda of Nagoya University and Prof. Kaoru Hirota of the Tokyo Institute of Technology for inviting us to serve as Guest Editors.

The 2010 International Symposium on Intelligent Systems (iFAN2010) was held at Tokyo Metropolitan University, Tokyo, Japan, in September 2010, in conjunction with the 20th anniversary of the 2010 Intelligent System Symposium (FAN2010). These two symposiums provided a fine opportunity for researchers to exchange ideas on basic theories and applications on intelligent systems and iFAN2010 was the first international symposium in the history of the FAN symposium.

From more than 200 papers of FAN2010 and iFAN2010, papers of top quality were invited to this special issue. From 17 papers submitted, 13 outstanding papers have been selected for this special issue after fair and peer review process. As these two symposiums covered a wide variety of intelligence-related issues, this special issue also consists of various topics from basic theories such as machine learning, adaptive control, and optimization, to application-oriented studies such as medical image processing, human support systems, and land mine detection. This issue is expected to contribute much to research on intelligent systems.

As the Editors of this special issue, we thank the contributors and reviewers for their time and cooperation. We look forward to actively participating to the next FAN2011, to be held at Kobe University, Hyogo, Japan, in September 2011, which we hope will be as successful and fruitful as the 2010 symposium.

Opportunities for human beings and robots to work together are increasing. The objective of this special issuefs ten articles is to activate and expand top-quality research.

In the first, T. Muto and Y. Miyake explore interpersonal cooperative walking replicated for two human beings and the motor-control mechanisms involved.

In the second, Y. Nishikawa, Y. Kagawa, and J. Kurabayashi study control of healthcare equipment and a manipulator using electromyography (EMG) signals.

The third contribution, by T. Hashimoto, Y. Takakura, T. Hamada, T. Akazawa, and M. Yamamoto, details a walking simulator using virtual reality.

The fourth, by Y. Tang, H. A. Vu, P. Q. Le, D. Masano, O. Thet, C. Fatichah, Z. Liu, M. Yamaguchi, M. L. Tangel, F. Dong, Y. Yamazaki, and K. Hirota, proposes casual communication between humans and robots by integrating nonverbal gestures and verbal messages.

Y. Ho, T. Shibano, E. Sato-Shimokawara, and T. Yamaguchi present a system in the fifth article that uses data mining to detect human intent collecting, processing, and analyzing human motion.

In the sixth, K. Rattanyu and M. Mizukawa introduce emotion recognition based on electrocardiography (ECG) signals.

In the seventh article, K. Ogawa, S. Nishio, K. Koda, G. Balistreri, T. Watanabe, and H. Ishiguro discusses two field tests using the Telenoid android.

The eighth contribution, by H. Suzuki and H. Nishi, shows how animal gaits are implemented by quadrupedal robots.

K. Zhang, Y. Maeda, and Y. Takahashi propose multiagent reinforcement learning in the ninth article.

The closing contribution, by B. Piriyanont, N. Uchiyama, and S. Sano, proposes collision avoidance control for a quadrocopter based on the social force model concept.

We thank the referees for their comprehensive reviews and the Fuji Technology Press Ltd. staff for its encouragement and advice.

The International Society of Management Engineers (ISME), founded in April 2003 to support ME innovation and research, covers methods and techniques related to industrial production and management, in contrast to conventional industrial engineering. Recent examples include innovative research on such topics as

· logistics,

· service,

· supply chain management,

· knowledge management.

These topics, among others, are part of ME. Other important ME areas are mobile business and e-commerce.

The ISME organized its first symposium in 2004, with such symposiums becoming a regular event. This special issue focuses on papers from the seventh International Symposium on Management Engineering ISMEf2010, held on August 26-28, 2010, in Kitakyushu, Japan. It also includes several related papers. ISME’2010 centered on “Management Engineering — Bridging the Gap between Humans and Systems.”

The symposiumfs topics include organization, corporate strategy, project management, technology management, intelligence, computation, operations research, probability and possibility theories, fuzzy sets, rough sets, approximate reasoning, linguistic information processing and automata, knowledge discovery, clustering and data analysis, fuzzy control and modeling, optimization under uncertainty and its applications, games and decision making, fuzzy analysis, and fuzzy games. These topics are reflected in this issue’s contributions.

We thank:

· the authors for their outstanding work,

· ISMEf2010 participants for their helpful suggestions,

· the reviewers for their thorough analysis and constructive help,

· Professor Junzo Watada for his kind suggestions in hosting this issue, and

· the journal staff for their tireless work.

Fuzzy Rule Interpolation (FRI) methods are well known tools for reasoning in case of insufficient knowledge expressed as sparse fuzzy rule-bases. It also provides a simple way to define fuzzy functions. Despite these advantages, FRI techniques are relatively rarely applied in practice.

Enabling sparse fuzzy rule-bases, FRI dramatically simplifies rule-base creation. Regardless of whether the rule-base is generated by a human expert, or automatically from input-output data, the ability to provide reasonable interpolated conclusions even if no rule fires for a given observation, help to concentrate on cardinal actions alone. This reduces the number of rules needed, speeds up parameter optimization and validation steps, and hence simplifies rule-base creation itself.

This special issuefs six papers take six different directions in current FRI research.

The first introduces the FRI concept and sets up a unified criteria and evaluation system. This work collects the main properties an FRI method generally has to fulfill. The next two papers are related to the constantly important mainstream research on the more and more sophisticated FRI methods, the endeavor of finding the best way for defining a fuzzy valued fuzzy function based on data given in the form of the relation of fuzzy sets, i.e., in fuzzy rules. The second paper introduces a novel FRI method that is able to handle fuzzy observations activating multiple rule antecedents applying the concept of nonlinear fuzzy-valued function. The third paper presents a novel ganalogical-basedh FRI method that rather fits into the traditional FRI research line, improving the n-rule-based gscale and move transformationh FRI to ensure continuous approximate functions. The fourth paper addresses the issue of defining a distance function between fuzzy sets on a domain that is not necessarily Euclidean metric space. In FRI, this takes on the importance if antecedent or consequent domains are non-Euclidean metric spaces. The last two papers discuss direct FRI control applications. One is an example proving that the sparse fuzzy rule-base is an efficient knowledge representation in intelligent control solutions. The last deals with the computational efficiency of implemented FRI methods applied to direct control area, clearly showing that the sparse fuzzy rule-base is not only a convenient way for knowledge representation, but also makes FRI methods possible devices for direct embedded control applications.

The 4th International Symposium on Computational Intelligence and Industrial Applications (ISCIIA2010), held at the Harbin University of Science and Technology in Heilongjiang Province, China, in August 2010 focused on advanced technologies for computational intelligence and industrial applications. A series of ISCIIA symposiums has provided a unique opportunity for the academic and industrial communities to address new challenges, share new-found solutions, and discuss directions for future research.

Of the ISCIIA2010fs 50 papers, 11 outstanding papers have been selected for this special issue after fair and strict review process. Among this issuefs topics are fuzzy logic,Web mining, Kansei Information Processing (KIP), brain informatics, and human-centered systems. Given the importance of these topics to both the academic and industrial communities, this issue should contribute much to active exchange between both communities.

As the Editor of this special issue, I thank all of the contributors and reviewers for their time and cooperation. Herefs hoping that the next ISCIIA, which is being held in Hokkaido, Japan, in 2012, will be as successful and fruitful as the 2010 symposium has been.

Agent-Based Simulation (ABS), an interdisciplinary area embracing both the computer science and the social science, has attracted much attention and aided the understanding of socially complex phenomena. A current important issue in this research area is how to improve ABS effectiveness and comprehension, which makes further mutual influence between the computer science and the social sciences indispensable – e.g., (1) agent modeling involving learning mechanisms in the computer science and (2) social dynamics analysis needed in the social science. Such integration of these two areas would help fulfill the great potential of ABS, first in solving complex engineering problems using agent-based technology and second in developing and testing new theories on socially complex systems.

This special issue features ABS papers from both of these important areas exploring new trends in ABS. The 10 papers composing this special issue start with papers by Nobutada Fujii and Hiroyasu Inoue analyzing the relationship between the network structure and system dynamics. In these papers, an agent-based computational economics approach has been active in applying agent-based technologies to financial and economic systems. Papers by Biliana Alexandrova-Kabadjova, Isamu Okada, TomokoOhi, and Nariaki Nishino cover consumer and financial markets using agent-based models. They test economic theory and examine market phenomena for market design. Agent-based simulation is increasingly used in application fields in the social sciences. Papers by Kiyoshi Izumi, Hideki Fujii, Hiromitsu Hattori, and Shigeo Sagai propose solutions for actual social problems such as injury prevention, traffic, and electrical power. Models are created based on behavior data, and the integration of an agent-based model and real data is a hot topic in this area.

As the beginning of these technical papers, this issue starts by a position paper to give an ABS overview for understanding important issues in ABS from an overall viewpoint and for understanding state-of-the-art ABS. The information presented is invaluable in helping readers grasp the important features of ABS.

The 6th International Conference on Modeling Decisions for Artificial Intelligence (MDAI) was held at Awaji Island, Japan, from November 30 to December 2, 2009 and was the inspiration for this special issue.

The nine selected papers concern soft computing tool applications.

The first, by Yoshida, studies the risk analysis of portfolios under uncertainty and gives expressions showing explicit relationships among parameters in a portfolio.

The second, by Entani, proposes an efficiency-interval-based measure based on interval data envelopment analysis.

The third, by Hamasuna, Endo, and Miyamoto, concerns clustering for data with tolerance and proposes algorithms for this type of data.

The fourth, by Endo, Hasegawa, Hamasuna, and Kanzawa, focuses on fuzzy c-means clustering for uncertain data using quadratic regularization.

The fifth, by Honda, Notsu, and Ichihashi, also involves clustering, focusing on variable selection/weighting in PCA-guided k-means.

The sixth, by Hwang and Miyamoto, covers clustering focusing on kernel fuzzy c-means and some interesting new results.

The seventh, by Kanzawa, Endo, and Miyamoto, uses fuzzy c-means in semisupervised fuzzy c-means.

The eighth, by Kudo and Murai, is devoted to rough sets, proposing a heuristic algorithm for calculating a relative reduct candidate.

The closing contribution, by Kusunoki and Inuiguchi, is also devoted to rough sets, with the authors studying rough set models in information tables with missing values.

We thank the referees for their review work, and the Fuji Technology Press Ltd. staff for its encouragement and advice.

With opportunities for human beings to coexist with artificial agents and autonomous robots are increasing, high-level interactive communication between them is increasingly needed. These human symbiotic systems are used for research on basic intelligent interaction design principles and methods and bidirectional communication based on effective collaboration and symbiosis between human beings and robots, agents, and computers, also known as artifacts.

The research society on gHuman Symbiotic System (HSS)h was implemented by the Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT) in 2007. The HSS encourages academic and industrial discussion of research on Human-Agent Interaction (HAI), Human-Robot Interaction (HRI), and Human-Computer Interaction (HCI).

The objective of this special issue is to activate and expand top-quality research of HSS theory and applications. Reflecting the fact that this research covers a wide range of topics, we invited researchers from fields including intelligent robotics, human-machine interfaces, and Kansei engineering to contribute. This issue thus provides much of the latest practical research on HSS, introduced by core members of the research society.

Of the 22 papers received, 14 were accepted after input from two reviewers each. The first paper, by Y. Tamura et al., presents an attentive deskwork support system that delivers required items objects to deskworkers. The second, by H. Masuta et al., discusses an integrated perceptual system for intelligent service robots. The third, by S. Akiguchi, develops an automatic pattern generation system based on user impression. The fourth, by Y. Jiang et al., deals with a novel interface recognizing directional user intent based on forearm pressure exerted by the user of an omnidirectional walker.

The fifth paper, by K. Terabayashi et al., investigates effects of preoperation on the experience of hands of different sizes by classifying preoperations based on the hand/object relationship. The sixth, by Y. Tamura et al., proposes segmenting a performerfs body imitating behavior observed based on a system from which values are obtained by reinforcement learning. The seventh, by D. Katagami et al., discusses group-adaptive behavior based on utterance contents and social standing of a robot. The eighth, by H. Yamaguchi et al., presents a system for using discounted utterances in spontaneous conversations applying text-mining technology.

The ninth paper, by A. Otaki et al., focuses on the development of human negotiation skill through interaction between human players and computer agents in bargaining games. The tenth, by D. Katagami et al., is also related to human negotiation skill implementing human gestures in negotiation scenarios for three negotiation agents. The eleventh, by R. Taki et al., realizes interactive emotion communication – bidirectional communication based on emotional behavior between human beings and robots. The twelfth, by J. Ichino et al., investigates the psychological effects of color on online documents through a proposed online document interface.

The thirteenth paper, by T. Ando et al., studies the robot facial effectiveness in human interpretation. The fourteenth, by T. Ando et al., models robot self-sufficiency applying an urge system focusing on autonomous emotion.

This issue has addressed the importance of HSS and highlighted innovative approaches to the development of artificial system more friendly to users. We thank the authors and referees for their ongoing efforts, without which this issue would not have been possible.